from sklearn_benchmarks.reporting.hp_match import HPMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HPMatchReporting(against_lib="sklearnex", config="config.yml")
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time sklearnex. For instance, a speedup of 2 means that sklearnex is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | n_samples_train | n_samples | n_features | accuracy_score_sklearn | accuracy_score_sklearnex | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 0.663 | 0.687 | 0.024 |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 0.757 | 0.742 | 0.015 |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 0.882 | 0.875 | 0.007 |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 1.000 | 0.000 | 1.000 |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 0.882 | 0.875 | 0.007 |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 1.000 | 0.000 | 1.000 |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 0.757 | 0.742 | 0.015 |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 0.663 | 0.687 | 0.024 |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 0.896 | 0.967 | 0.071 |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 0.922 | 0.974 | 0.052 |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 0.929 | 0.975 | 0.046 |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 0.929 | 0.975 | 0.046 |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 0.922 | 0.974 | 0.052 |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 0.896 | 0.967 | 0.071 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.000 | NaN | 6.207 | 0.0 | -1 | 1 | NaN | 0.053 | 0.004 | NaN | 0.245 | 0.246 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.000 | NaN | 6.176 | 0.0 | -1 | 5 | NaN | 0.054 | 0.002 | NaN | 0.239 | 0.239 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.000 | NaN | 6.302 | 0.0 | 1 | 100 | NaN | 0.051 | 0.002 | NaN | 0.249 | 0.249 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.014 | 0.000 | NaN | 5.535 | 0.0 | -1 | 100 | NaN | 0.056 | 0.002 | NaN | 0.259 | 0.259 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.001 | NaN | 6.126 | 0.0 | 1 | 5 | NaN | 0.055 | 0.001 | NaN | 0.239 | 0.239 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.000 | NaN | 5.974 | 0.0 | 1 | 1 | NaN | 0.057 | 0.005 | NaN | 0.233 | 0.234 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | NaN | 0.334 | 0.0 | -1 | 1 | NaN | 0.009 | 0.000 | NaN | 0.545 | 0.546 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | NaN | 0.344 | 0.0 | -1 | 5 | NaN | 0.009 | 0.000 | NaN | 0.527 | 0.528 | See | See |
| 24 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | NaN | 0.312 | 0.0 | 1 | 100 | NaN | 0.009 | 0.000 | NaN | 0.570 | 0.570 | See | See |
| 27 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | NaN | 0.327 | 0.0 | -1 | 100 | NaN | 0.009 | 0.000 | NaN | 0.524 | 0.524 | See | See |
| 30 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | NaN | 0.319 | 0.0 | 1 | 5 | NaN | 0.009 | 0.001 | NaN | 0.550 | 0.551 | See | See |
| 33 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | NaN | 0.340 | 0.0 | 1 | 1 | NaN | 0.009 | 0.000 | NaN | 0.524 | 0.524 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.059 | 0.120 | NaN | 0.000 | 0.002 | -1 | 1 | 0.663 | 0.404 | 0.012 | 0.687 | 5.097 | 5.099 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.027 | 0.004 | NaN | 0.000 | 0.027 | -1 | 1 | 1.000 | 0.011 | 0.000 | 1.000 | 2.475 | 2.475 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.870 | 0.062 | NaN | 0.000 | 0.003 | -1 | 5 | 0.757 | 0.401 | 0.009 | 0.742 | 7.149 | 7.151 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.027 | 0.003 | NaN | 0.000 | 0.027 | -1 | 5 | 1.000 | 0.011 | 0.000 | 1.000 | 2.521 | 2.522 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.235 | 0.026 | NaN | 0.000 | 0.002 | 1 | 100 | 0.882 | 0.450 | 0.005 | 0.875 | 4.971 | 4.971 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.025 | 0.001 | NaN | 0.000 | 0.025 | 1 | 100 | 1.000 | 0.011 | 0.000 | 0.000 | 2.300 | 2.300 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.878 | 0.070 | NaN | 0.000 | 0.003 | -1 | 100 | 0.882 | 0.457 | 0.019 | 0.875 | 6.297 | 6.302 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.028 | 0.005 | NaN | 0.000 | 0.028 | -1 | 100 | 1.000 | 0.012 | 0.001 | 0.000 | 2.424 | 2.443 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.242 | 0.020 | NaN | 0.000 | 0.002 | 1 | 5 | 0.757 | 0.409 | 0.014 | 0.742 | 5.489 | 5.492 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.025 | 0.002 | NaN | 0.000 | 0.025 | 1 | 5 | 1.000 | 0.011 | 0.000 | 1.000 | 2.302 | 2.304 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.416 | 0.018 | NaN | 0.001 | 0.001 | 1 | 1 | 0.663 | 0.406 | 0.011 | 0.687 | 3.483 | 3.484 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.022 | 0.001 | NaN | 0.000 | 0.022 | 1 | 1 | 1.000 | 0.011 | 0.000 | 1.000 | 2.005 | 2.007 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.717 | 0.042 | NaN | 0.000 | 0.002 | -1 | 1 | 0.896 | 0.084 | 0.002 | 0.967 | 20.487 | 20.495 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.004 | 0.000 | NaN | 0.000 | 0.004 | -1 | 1 | 1.000 | 0.001 | 0.000 | 1.000 | 7.598 | 7.617 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.651 | 0.050 | NaN | 0.000 | 0.003 | -1 | 5 | 0.922 | 0.087 | 0.003 | 0.974 | 30.421 | 30.444 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.008 | 0.003 | NaN | 0.000 | 0.008 | -1 | 5 | 1.000 | 0.001 | 0.000 | 1.000 | 11.895 | 12.362 | See | See |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.137 | 0.035 | NaN | 0.000 | 0.002 | 1 | 100 | 0.929 | 0.141 | 0.005 | 0.975 | 15.202 | 15.214 | See | See |
| 26 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.004 | 0.000 | NaN | 0.000 | 0.004 | 1 | 100 | 1.000 | 0.001 | 0.000 | 1.000 | 5.179 | 5.374 | See | See |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.627 | 0.026 | NaN | 0.000 | 0.003 | -1 | 100 | 0.929 | 0.138 | 0.005 | 0.975 | 19.044 | 19.055 | See | See |
| 29 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.006 | 0.002 | NaN | 0.000 | 0.006 | -1 | 100 | 1.000 | 0.001 | 0.000 | 1.000 | 9.596 | 9.626 | See | See |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.057 | 0.021 | NaN | 0.000 | 0.002 | 1 | 5 | 0.922 | 0.088 | 0.004 | 0.974 | 23.376 | 23.395 | See | See |
| 32 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | 1 | 5 | 1.000 | 0.001 | 0.000 | 1.000 | 5.245 | 5.262 | See | See |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.175 | 0.018 | NaN | 0.000 | 0.001 | 1 | 1 | 0.896 | 0.084 | 0.003 | 0.967 | 13.910 | 13.920 | See | See |
| 35 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | 1 | 1 | 1.000 | 0.001 | 0.000 | 1.000 | 3.692 | 3.698 | See | See |
KNeighborsClassifier_kd_tree¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | n_samples_train | n_samples | n_features | accuracy_score_sklearn | accuracy_score_sklearnex | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.929 | 0.910 | 0.019 |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.946 | 0.941 | 0.005 |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.951 | 0.940 | 0.011 |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.951 | 0.940 | 0.011 |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.946 | 0.941 | 0.005 |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.929 | 0.910 | 0.019 |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.891 | 0.879 | 0.012 |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.911 | 0.905 | 0.006 |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.894 | 0.917 | 0.023 |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.894 | 0.917 | 0.023 |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.911 | 0.905 | 0.006 |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.891 | 0.879 | 0.012 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2.917 | 0.026 | NaN | 0.027 | 0.0 | -1 | 1 | NaN | 0.789 | 0.027 | NaN | 3.698 | 3.700 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.631 | 0.071 | NaN | 0.017 | 0.0 | -1 | 5 | NaN | 0.773 | 0.009 | NaN | 5.993 | 5.994 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.359 | 0.060 | NaN | 0.018 | 0.0 | 1 | 100 | NaN | 0.737 | 0.013 | NaN | 5.911 | 5.912 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.757 | 0.158 | NaN | 0.017 | 0.0 | -1 | 100 | NaN | 0.761 | 0.013 | NaN | 6.252 | 6.253 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.356 | 0.145 | NaN | 0.018 | 0.0 | 1 | 5 | NaN | 0.726 | 0.018 | NaN | 5.998 | 6.000 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.622 | 0.054 | NaN | 0.017 | 0.0 | 1 | 1 | NaN | 0.762 | 0.011 | NaN | 6.063 | 6.063 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | NaN | 0.018 | 0.0 | -1 | 1 | NaN | 0.004 | 0.002 | NaN | 0.227 | 0.258 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.024 | 0.0 | -1 | 5 | NaN | 0.001 | 0.001 | NaN | 0.510 | 0.613 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.023 | 0.0 | 1 | 100 | NaN | 0.001 | 0.001 | NaN | 0.637 | 0.709 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.025 | 0.0 | -1 | 100 | NaN | 0.001 | 0.000 | NaN | 0.643 | 0.648 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.024 | 0.0 | 1 | 5 | NaN | 0.001 | 0.000 | NaN | 0.671 | 0.673 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.025 | 0.0 | 1 | 1 | NaN | 0.001 | 0.000 | NaN | 0.659 | 0.662 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.851 | 1.033 | NaN | 0.000 | 0.001 | -1 | 1 | 0.929 | 0.128 | 0.004 | 0.910 | 6.649 | 6.652 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | -1 | 1 | 1.000 | 0.000 | 0.000 | 1.000 | 10.879 | 11.267 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.094 | 0.351 | NaN | 0.000 | 0.001 | -1 | 5 | 0.946 | 0.230 | 0.006 | 0.941 | 4.761 | 4.763 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | NaN | 0.000 | 0.003 | -1 | 5 | 1.000 | 0.000 | 0.000 | 1.000 | 7.410 | 7.647 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.830 | 0.494 | NaN | 0.000 | 0.006 | 1 | 100 | 0.951 | 0.694 | 0.018 | 0.940 | 8.397 | 8.400 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | NaN | 0.000 | 0.003 | 1 | 100 | 1.000 | 0.001 | 0.000 | 1.000 | 4.054 | 4.182 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 3.376 | 0.283 | NaN | 0.000 | 0.003 | -1 | 100 | 0.951 | 0.691 | 0.016 | 0.940 | 4.886 | 4.887 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.006 | 0.001 | NaN | 0.000 | 0.006 | -1 | 100 | 1.000 | 0.001 | 0.000 | 1.000 | 6.679 | 6.913 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.880 | 0.392 | NaN | 0.000 | 0.002 | 1 | 5 | 0.946 | 0.232 | 0.009 | 0.941 | 8.121 | 8.126 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | 1 | 5 | 1.000 | 0.000 | 0.000 | 1.000 | 4.297 | 4.413 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.031 | 0.288 | NaN | 0.000 | 0.001 | 1 | 1 | 0.929 | 0.126 | 0.004 | 0.910 | 8.187 | 8.191 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 1 | 1.000 | 0.000 | 0.000 | 1.000 | 3.879 | 4.038 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.035 | 0.016 | NaN | 0.000 | 0.000 | -1 | 1 | 0.891 | 0.001 | 0.000 | 0.879 | 67.911 | 68.080 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | -1 | 1 | 1.000 | 0.000 | 0.000 | 1.000 | 17.792 | 17.993 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.034 | 0.003 | NaN | 0.000 | 0.000 | -1 | 5 | 0.911 | 0.001 | 0.000 | 0.905 | 43.130 | 43.159 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.001 | NaN | 0.000 | 0.003 | -1 | 5 | 1.000 | 0.000 | 0.000 | 1.000 | 21.435 | 21.722 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.045 | 0.006 | NaN | 0.000 | 0.000 | 1 | 100 | 0.894 | 0.006 | 0.001 | 0.917 | 8.101 | 8.136 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 100 | 1.000 | 0.000 | 0.000 | 1.000 | 5.408 | 5.478 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.048 | 0.006 | NaN | 0.000 | 0.000 | -1 | 100 | 0.894 | 0.006 | 0.002 | 0.917 | 7.319 | 7.538 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | -1 | 100 | 1.000 | 0.000 | 0.000 | 1.000 | 12.754 | 15.943 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.029 | 0.000 | NaN | 0.001 | 0.000 | 1 | 5 | 0.911 | 0.001 | 0.000 | 0.905 | 36.983 | 36.999 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 5 | 1.000 | 0.000 | 0.000 | 1.000 | 5.647 | 5.743 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.028 | 0.001 | NaN | 0.001 | 0.000 | 1 | 1 | 0.891 | 0.001 | 0.000 | 0.879 | 46.360 | 47.902 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 1 | 1.000 | 0.000 | 0.000 | 1.000 | 6.256 | 6.348 | See | See |
KMeans_tall¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.619 | 0.193 | 30 | 0.026 | 0.0 | random | NaN | 0.302 | 0.007 | NaN | 2.051 | 2.052 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.652 | 0.079 | 30 | 0.025 | 0.0 | k-means++ | NaN | 0.329 | 0.006 | NaN | 1.979 | 1.979 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 6.727 | 0.124 | 30 | 0.119 | 0.0 | random | NaN | 3.780 | 0.049 | NaN | 1.780 | 1.780 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 7.153 | 0.016 | 30 | 0.112 | 0.0 | k-means++ | NaN | 4.002 | 0.033 | NaN | 1.787 | 1.787 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.001 | 30 | 0.008 | 0.000 | random | 0.001 | 0.0 | 0.0 | 0.001 | 7.782 | 10.403 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | random | 1.000 | 0.0 | 0.0 | 1.000 | 10.315 | 10.437 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.000 | 30 | 0.009 | 0.000 | k-means++ | 0.001 | 0.0 | 0.0 | 0.001 | 7.943 | 8.668 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | k-means++ | 1.000 | 0.0 | 0.0 | 1.000 | 11.668 | 11.813 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.395 | 0.000 | random | 0.002 | 0.0 | 0.0 | 0.002 | 4.873 | 6.862 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | random | 1.000 | 0.0 | 0.0 | 1.000 | 10.449 | 10.601 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.394 | 0.000 | k-means++ | 0.002 | 0.0 | 0.0 | 0.001 | 7.288 | 7.556 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | k-means++ | 1.000 | 0.0 | 0.0 | 1.000 | 11.377 | 11.516 | See | See |
KMeans_short¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | adjusted_rand_score_sklearn | adjusted_rand_score_sklearnex | diff_adjusted_rand_scores | |
|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 0.000126 | -0.000965 | 0.001090 |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 0.001245 | -0.000750 | 0.001995 |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 0.278733 | 0.293767 | 0.015034 |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 0.317011 | 0.256968 | 0.060044 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 0.094 | 0.002 | 20 | 0.002 | 0.0 | random | NaN | 0.050 | 0.003 | NaN | 1.890 | 1.894 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 0.296 | 0.006 | 20 | 0.001 | 0.0 | k-means++ | NaN | 0.128 | 0.004 | NaN | 2.317 | 2.318 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 0.318 | 0.005 | 20 | 0.025 | 0.0 | random | NaN | 0.247 | 0.003 | NaN | 1.290 | 1.290 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 1.080 | 0.024 | 20 | 0.007 | 0.0 | k-means++ | NaN | 0.591 | 0.006 | NaN | 1.825 | 1.825 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.000 | 20 | 0.008 | 0.000 | random | 0.000 | 0.001 | 0.0 | -0.001 | 3.824 | 3.831 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | random | 1.000 | 0.000 | 0.0 | 1.000 | 8.263 | 9.882 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.000 | 20 | 0.007 | 0.000 | k-means++ | 0.001 | 0.001 | 0.0 | -0.001 | 3.692 | 3.710 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | k-means++ | 1.000 | 0.000 | 0.0 | 1.000 | 10.057 | 10.195 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.000 | 20 | 0.235 | 0.000 | random | 0.279 | 0.001 | 0.0 | 0.294 | 2.283 | 2.300 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | random | 1.000 | 0.000 | 0.0 | 1.000 | 8.569 | 8.684 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 0.004 | 0.001 | 20 | 0.224 | 0.000 | k-means++ | 0.317 | 0.001 | 0.0 | 0.257 | 2.442 | 2.456 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | k-means++ | 1.000 | 0.000 | 0.0 | 1.000 | 9.312 | 9.491 | See | See |
LogisticRegression¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | n_samples_train | n_samples | n_features | accuracy_score_sklearn | accuracy_score_sklearnex | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 0.56 | 0.55 | 0.01 |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 0.35 | 0.28 | 0.07 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 15.972 | 0.564 | [20] | 0.050 | 0.000 | NaN | NaN | NaN | NaN | NaN | 2.91 | 0.048 | NaN | 5.489 | 5.490 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 1.419 | 0.700 | [26] | 0.056 | 0.001 | NaN | NaN | NaN | NaN | NaN | 1.12 | 0.032 | NaN | 1.267 | 1.267 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 0.001 | 0.000 | [20] | 1.560 | 0.0 | NaN | NaN | NaN | NaN | 0.56 | 0.001 | 0.001 | 0.55 | 0.625 | 1.233 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 0.000 | 0.000 | [20] | 0.010 | 0.0 | NaN | NaN | NaN | NaN | 1.00 | 0.000 | 0.000 | 1.00 | 0.360 | 0.362 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 0.002 | 0.000 | [26] | 3.452 | 0.0 | NaN | NaN | NaN | NaN | 0.35 | 0.008 | 0.001 | 0.28 | 0.296 | 0.297 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 0.000 | 0.001 | [26] | 0.183 | 0.0 | NaN | NaN | NaN | NaN | 0.00 | 0.002 | 0.000 | 0.00 | 0.248 | 0.248 | See | See |
Ridge¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | n_samples_train | n_samples | n_features | r2_score_sklearn | r2_score_sklearnex | diff_r2_scores | |
|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 0.082567 | 0.122191 | 0.039624 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | max_iter | random_state | r2_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | r2_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 0.294 | 0.006 | NaN | 0.272 | 0.0 | NaN | NaN | NaN | 0.304 | 0.006 | NaN | 0.967 | 0.967 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 1.277 | 0.068 | NaN | 0.627 | 0.0 | NaN | NaN | NaN | 0.428 | 0.263 | NaN | 2.984 | 3.502 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | max_iter | random_state | r2_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | r2_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 0.012 | 0.0 | NaN | 6.662 | 0.0 | NaN | NaN | 0.083 | 0.02 | 0.001 | 0.122 | 0.594 | 0.594 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | NaN | 0.900 | 0.0 | NaN | NaN | NaN | 0.00 | 0.000 | NaN | 0.600 | 0.612 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | NaN | 4.919 | 0.0 | NaN | NaN | 1.000 | 0.00 | 0.000 | 1.000 | 0.451 | 0.637 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | NaN | 0.009 | 0.0 | NaN | NaN | NaN | 0.00 | 0.000 | NaN | 0.715 | 0.738 | See | See |